Electronic trading is offered in many different markets, and is a well known means of matching orders to buy and sell items in the market. Matched orders can be then be electronically “executed” in order to implement those matched orders. Electronic trading platforms necessarily require technical resources in order to effect these electronic trades. Ongoing optimization of the hardware and software resources of electronic trading platforms has the technical effect of reducing loads on those hardware and software resources, and at the same time leading to an overall improvement in quality of electronic trades, such quality being indicated by speed (e.g. reduced network latency), efficiency (e.g. reduced processing resources on a central processing unit, reduced electronic memory consumption), accuracy (e.g. the actual quoted value for a given item is correct) and the like.
Different types of electronic trades are characterized by different data record structures that represent the traded instrument. Such variations in data record structures lead to unique technical structures and configurations that correspond to the different types of electronic trades. Furthermore, the network interconnections between servers involved in the electronic trading, and the configuration of the hardware and software processes on those electronic trading servers also impacts the quality of different types of electronic trades.
One type of electronic trading is characterized by data records that are structured to represent bonds. Bond data records are often maintained in different formats within different computing environments that are each maintained by different dealers. Electronic quotations associated with bond data records need to be updated on a periodic basis, typically daily, and made available to all dealers of bonds associated with certain bond data records.
In certain current configurations, one example of which is the electronic trading of bonds in Canada, computing environments maintained by certain trading firms or dealers rely only on electronic trading data associated with that one computing environment, and do not interact with electronic trading data associated with computing environments maintained by other dealers. This leads to electronic quotations within the computing environment of one dealer that are heterogeneous in relation to the electronic computing environments of other dealers. In other configurations, computing environments of different dealers may be networked in some fashion or another, so that electronic trading data of all dealers can be examined to ascertain an electronic quote respective to a complete set of bond data records respective to a given bond as maintained in computing environments associated with the participating dealers. However, excessive computing resources can be consumed in examining all bond data records respective to a given bond. Furthermore, excessive consumption of computing resources can also interfere with other networked computing resources that are dedicated to ultimately effecting electronic trades based on timely and meaningful electronic quotes. It is therefore desirable to reduce the computing resource burden associated with examining and processing bond data records respective to a given bond in order to generate an electronic quote for that bond.